Jamie R Robinson1,2, Robert J Carroll3, Lisa Bastarache3, Qingxia Chen4, Zongyang Mou3, Wei-Qi Wei3, John J Connolly5, Frank Mentch5, Patrick Sleiman5, Paul K Crane6, Scott J Hebbring7, Ian B Stanaway8, David R Crosslin8, Adam S Gordon9, Elisabeth A Rosenthal9, David Carrell10, M Geoffrey Hayes11, Wei Wei12, Lynn Petukhova13, Bahram Namjou14, Ge Zhang15,16, Maya S Safarova17, Nephi A Walton18, Christopher Still18, Erwin P Bottinger19, Ruth J F Loos19, Shawn N Murphy20, Gretchen P Jackson3,21, Iftikhar J Kullo17, Hakon Hakonarson5, Gail P Jarvik9, Eric B Larson10, Chunhua Weng22, Dan M Roden3,23,24, Joshua C Denny3,23. 1. Department of Biomedical Informatics, Vanderbilt University Medical Center, 1161 21st Ave S, CCC-4312 MCN, Nashville, TN, 37232-2730, USA. jamie.r.robinson@vumc.org. 2. Department of Surgery, Vanderbilt University Medical Center, Nashville, TN, USA. jamie.r.robinson@vumc.org. 3. Department of Biomedical Informatics, Vanderbilt University Medical Center, 1161 21st Ave S, CCC-4312 MCN, Nashville, TN, 37232-2730, USA. 4. Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA. 5. The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA. 6. Department of Medicine, University of Washington, Seattle, WA, USA. 7. Center for Human Genetics, Marshfield Clinic Research Institute, Marshfield, WI, USA. 8. Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA. 9. Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA, USA. 10. Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA. 11. Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. 12. University of Pittsburgh Medical Center, Pittsburgh, PA, USA. 13. Departments of Dermatology and Epidemiology, Columbia University, New York, NY, USA. 14. Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 15. Division of Human Genetics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA. 16. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA. 17. Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA. 18. Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, USA. 19. The Charles Bronfman Institute for Personalized Medicine at Mount Sinai, The Mindich Child Health and Development Institute, New York, NY, USA. 20. Department of Neurology, Partners Healthcare, Boston, MA, USA. 21. Department of Pediatric Surgery, Vanderbilt University Medical Center, Nashville, TN, USA. 22. Department of Biomedical Informatics, Columbia University, New York, NY, USA. 23. Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. 24. Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA.
Abstract
BACKGROUND: The extent to which obesity and genetics determine postoperative complications is incompletely understood. METHODS: We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components. RESULTS: Individuals with overweight or obese BMI (≥25 kg/m2) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10-20), and people with obesity (BMI ≥ 30 kg/m2) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10-5). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10-6) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10-6). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures. CONCLUSIONS: Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.
BACKGROUND: The extent to which obesity and genetics determine postoperative complications is incompletely understood. METHODS: We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990 and 2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records and Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score was constructed from 97 obesity-risk single-nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk of obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components. RESULTS: Individuals with overweight or obese BMI (≥25 kg/m2) had increased risk of incisional hernia (odds ratio [OR] 1.7-5.5, p < 3.1 × 10-20), and people with obesity (BMI ≥ 30 kg/m2) had increased risk of postoperative infection (OR 1.2-2.3, p < 2.5 × 10-5). In the eMERGE cohort, genetically predicted BMI was associated with incisional hernia (OR 2.1 [95% CI 1.8-2.5], p = 1.4 × 10-6) and postoperative infection (OR 1.6 [95% CI 1.4-1.9], p = 3.1 × 10-6). Association findings were similar after limitation of the cohorts to those who underwent abdominal procedures. CONCLUSIONS: Clinical and Mendelian randomization studies suggest that obesity, as measured by BMI, is associated with the development of postoperative incisional hernia and infection.
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